Current Health Status Certification

ABSTRACT

A technology is described for providing a determination regarding a person&#39;s health while maintaining privacy. In one example, health metrics for a person can be securely collected from sensor devices in communication with a mobile computing device during a baseline time period and baseline health metrics and a baseline health status can be defined using the one or more health metrics. Thereafter, a request for a current health status for the person can be received and current health metrics can be obtained for the person from sensor devices in communication with the mobile computing device. The current health metrics can be compared to the baseline health metrics to define the current health status for the person, and a certification message can be generated to be provided to a third-party certifying the current health status for the person.

FIELD OF THE TECHNOLOGY

The present technology relates to improved systems, methods, and devicesfor estimating a health status of an individual person. Moreparticularly, the present technology relates to systems, methods, anddevices for estimating a current health status of a person by comparingcurrent health metrics to baseline health metrics and generating acertification message certifying the current health status for theperson, which may be provided to a third-party, such as for point ofaccess admittance.

BACKGROUND OF THE TECHNOLOGY

The risks associated with contracting and disseminating an infectiousdisease through public contact have posed challenges to developingpublic policy for commercial locales, group gatherings and confinedtravel. The difficulty of assessing the health state of a person who isasymptomatic, exhibits mild symptoms, or masks symptoms has led topublic policy that can be prohibitive and can have detrimental effectson the economy and individual mental health. As an example, because ofthe potential of an infected person to communicate an infectious diseaseto others, public policy may prohibit gatherings of persons, limitgatherings to a limited number of persons, or prohibit or limit accessof persons to certain commercial locales, such as restaurants, retailand other stores, entertainment venues, and others. As another example,due to a public fear of contracting an infectious disease, persons mayavoid confined travel (e.g., air travel, metros, trains, busses, taxies,etc.). Determining a health status of a subject often requires adiagnosis by a medical practitioner during a physical or virtual officevisit. However, the health status of a person may be detected withoutthe assistance of a medical practitioner to place the person on noticethat public contact or interaction should be avoided and the personshould not enter public locations where the person could transmit aninfectious disease.

SUMMARY OF THE INVENTION

In light of the problems and deficiencies inherent in the prior art,disclosed herein are systems, methods, and devices configured to monitorindicators of health for a person and use those indicators to determinea current health state of the person and generate a health certificationmessage indicating the current health state. Such a certificationmessage can be conveyed to a third-party, such as to enable thethird-party to permit or deny point of access admittance of the person,or in other words, admittance of the person to a locale, area, activity,object, etc. overseen by the third-party. In one example discussedherein, a method for providing a determination regarding a person'shealth while maintaining privacy, can include collecting, at a mobilecomputing device, one or more health metrics for a person from sensordevices in communication with the mobile computing device during abaseline time period. The method can further include the operation ofdefining baseline health metrics and a baseline health status using theone or more health metrics. A request for a current health status forthe person can be received. The method can further comprise obtainingone or more current health metrics for the person from the mobilecomputing device, or the sensor devices in communication with the mobilecomputing device, wherein the current health metrics are obtained duringa current time period. The method may further comprise comparing thecurrent health metrics to the baseline health metrics to define thecurrent health status for the person. And the method can furthercomprise generating a certification message at the mobile computingdevice. In one aspect, the certification message can be provided to athird-party to facilitate a determination by the third-party whether ornot the person should be granted point of access admittance overseen bythe third-party. In one example, a photograph of the person can bedisplayed with the certification message. The photograph can provideverification of the identity of the person.

In one aspect of the technology, a mobile computing device can provide adetermination regarding a person's health while maintaining privacy. Themobile computing device can comprise at least one processor, and aplurality of sensor devices to monitor a person's medical metrics,wherein the plurality of sensor devices are in communication with themobile computing device. The mobile computing device may include atleast one memory device having a data store to store a plurality of dataand instructions that, when executed, cause the mobile computing deviceto collect one or more health metrics for a person from the plurality ofsensor devices in communication with the mobile computing device duringa baseline time period. The instructions, when executed, cause themobile computing device to further define baseline health metrics and abaseline health status using the one or more health metrics. Theinstructions, when executed, cause the mobile computing device tofurther receive a request for a current health status for the person.The mobile computing device can further receive current health metricsfor the person from the plurality of sensor devices in communicationwith the mobile computing device, and the current health metrics areobtained during a current time period. In addition, the mobile computingdevice can further compare the current health metrics to the baselinehealth metrics to define a current health status for the person. Themobile computing device can display a certification message certifyingthe person's current health status on a screen of the mobile computingdevice. In one aspect, the certification message can be provided to athird-party, such as to facilitate a determination by the third-partywhether or not the person should be granted point of access admittance.

In one aspect of the technology, a non-transitory machine readablestorage medium having instructions embodied thereon, the instructionswhen executed by one or more processors, cause the one or moreprocessors to perform a process comprising receiving one or more healthmetrics for a person from a plurality of sensor devices in communicationwith a mobile computing device during a baseline time period. Theprocess further comprises defining baseline health metrics and abaseline health status using the one or more health metrics. The processfurther can include the operation of receiving a request for a currenthealth status for the person. Current health metrics for the person fromthe plurality of sensor devices in communication with the mobilecomputing device can be received, and the current health metrics areobtained during a current time period. The process further includescomparing the current health metrics to the baseline health metrics todefine a current health status for the person. In addition, acertification message certifying the current health status of the personmay be displayed on a screen of the mobile computing device to enablethe certification message to be provided to a third-party.

BRIEF DESCRIPTION OF THE DRAWINGS

The present technology will become more fully apparent from thefollowing description and appended claims, taken in conjunction with theaccompanying drawings. Understanding that these drawings merely depictexemplary aspects of the present technology they are, therefore, not tobe considered limiting of its scope. It will be readily appreciated thatthe components of the present technology, as generally described andillustrated in the figures herein, could be arranged and designed in awide variety of different configurations. Nonetheless, the technologywill be described and explained with additional specificity and detailthrough the use of the accompanying drawings in which:

FIG. 1 is a diagram illustrating aspects of the present technology forproviding a determination regarding a person's health while maintainingprivacy.

FIG. 2 is a block diagram that illustrates a system environment thatincludes a mobile computing device used in accordance with an example ofthe present technology.

FIG. 3 is a diagram illustrating another system environment thatincludes a third-party mobile computing device used in accordance withan example of the present technology.

FIG. 4 is a diagram that illustrates another system environment thatincludes a health check station used in accordance with an example ofthe present technology.

FIG. 5 is a flow diagram illustrating an example method for providing acurrent health status of a person.

FIG. 6 is block diagram illustrating an example of a computing devicethat may be used to execute a method for determining a current healthstatus for a person.

DETAILED DESCRIPTION OF EXEMPLARY ASPECTS OF THE TECHNOLOGY

The following detailed description of exemplary aspects of thetechnology makes reference to the accompanying drawings, which form apart hereof and in which are shown, by way of illustration, exemplaryaspects in which the technology can be practiced. While these exemplaryaspects are described in sufficient detail to enable those skilled inthe art to practice the technology, it should be understood that otheraspects can be realized and that various changes to the technology canbe made without departing from the spirit and scope of the presenttechnology. Thus, the following more detailed description of the aspectsof the present technology is not intended to limit the scope of thetechnology, as claimed, but is presented for purposes of illustrationonly and not limitation to describe the features and characteristics ofthe present technology, to set forth the best mode of operation of thetechnology, and to sufficiently enable one skilled in the art topractice the technology. Accordingly, the scope of the presenttechnology is to be defined solely by the appended claims. The followingdetailed description and exemplary aspects of the technology will bebest understood by reference to the accompanying drawings anddescription, wherein the elements and features of the technology aredesignated by numerals throughout the drawings and described herein.

As used in this specification and the appended claims, the singularforms “a,” “an” and “the” include plural referents unless the contextclearly dictates otherwise. Thus, for example, reference to “a layer”includes a plurality of such layers.

The terms “first,” “second,” “third,” “fourth,” and the like in thedescription and in the claims, if any, are used for distinguishingbetween similar elements and not necessarily for describing a particularsequential or chronological order. It is to be understood that any termsso used are interchangeable under appropriate circumstances such thatthe embodiments described herein are, for example, capable of operationin sequences other than those illustrated or otherwise described herein.Similarly, if a method is described herein as comprising a series ofsteps, the order of such steps as presented herein is not necessarilythe only order in which such steps can be performed, and certain of thestated steps can possibly be omitted and/or certain other steps notdescribed herein can possibly be added to the method.

As used herein, the term “substantially” refers to the complete ornearly complete extent or degree of an action, characteristic, property,state, structure, item, or result. For example, an object that is“substantially” enclosed would mean that the object is either completelyenclosed or nearly completely enclosed. The exact allowable degree ofdeviation from absolute completeness can in some cases depend on thespecific context. However, generally speaking the nearness of completionwill be so as to have the same overall result as if absolute and totalcompletion were obtained. The use of “substantially” is equallyapplicable when used in a negative connotation to refer to the completeor near complete lack of an action, characteristic, property, state,structure, item, or result. For example, a composition that is“substantially free of” particles would either completely lackparticles, or so nearly completely lack particles that the effect wouldbe the same as if it completely lacked particles. In other words, acomposition that is “substantially free of” an ingredient or element canstill actually contain such item as long as there is no measurableeffect thereof.

As used herein, the term “about” is used to provide flexibility to arange endpoint by providing that a given value can be “a little above”or “a little below” the endpoint. Unless otherwise stated, use of theterm “about” in accordance with a specific number or numerical rangeshould also be understood to provide support for such numerical terms orrange without the term “about”. For example, for the sake of convenienceand brevity, a numerical range of “about 50 to about 80” should also beunderstood to provide support for the range of “50 to 80.”

An initial overview of technology is provided below and specifictechnology is then described in further detail. This initial summary isintended to aid readers in understanding the technology more quickly,but is not intended to identify key or essential features of thetechnology, nor is it intended to limit the scope of the claimed subjectmatter.

The technology described herein includes systems, methods, and devicesfor providing a determination regarding a person's health whilemaintaining privacy of health metrics for the person. In one example ofthe technology, a mobile computing device can be configured to collectone or more health metrics for a person from sensor devices incommunication with the mobile computing device (e.g., sensors containedin the mobile computing device and/or in wired or wireless communicationwith the mobile computing device) during a baseline time period. The oneor more health metrics collected by the mobile computing device can beused to define baseline health metrics and a baseline health status fora person. The mobile computing device can receive requests for a currenthealth status for the person. In response, the mobile computing devicecan obtain one or more current health metrics for the person from one ormore of the sensor devices in communication with the mobile computingdevice during a current time period. The current health metrics can becompared to the baseline health metrics to define the current healthstatus for the person and a certification message indicating the currenthealth status of the person can be generated at the mobile computingdevice. The certification message can be provided to a third-party tocertify the current health status for the person.

In another example of the technology, a mobile computing device can beused by a third-party to obtain current health metrics from a person andthe current health metrics can be sent to a data center to be used todefine a current health status for the person. The current health statusmay be defined by comparing the current health metrics to baselinehealth metrics for the person. A certification message indicating thecurrent health status of the person can be generated at the data center,and the certification message can be sent from the data center to themobile computing device to allow the third-party to view thecertification message.

In another example of the technology, a health check station containinga plurality of sensor devices can be used to obtain current healthmetrics for a person and send the current health metrics to a datacenter to be used to define a current health status for the person. Thecurrent health status may be defined by comparing the current healthmetrics to baseline health metrics for the person. A certificationmessage indicating the current health status of the person can begenerated at the data center, and the certification message can be sentfrom the data center to the health check station to allow a third-partyto view the certification message.

To further describe the present technology, examples are now providedwith reference to the figures. FIG. 1 is a diagram illustrating ahigh-level example for providing a determination regarding a person'shealth while maintaining privacy. As illustrated, a mobile computingdevice 102 can be configured to provide an indication of a currenthealth status for a person 104. The mobile computing device 102 caninclude a smart phone, a smart watch, a tablet, a laptop, a digitalassistant, a mobile internet device, a wearable device, or anotherappropriate mobile computing device. The mobile computing device 102 maybe kept on or in proximity of a person 102 and the mobile computingdevice 102 can collect one or more health metrics from sensor devicescontained in the mobile computing device 102 and/or connected to themobile computing device 102 via a wired or wireless connection.

A sensor device or system can include: a camera sensor, a heart ratesensor, a respiration rate sensor, an acoustic emission sensor, atemperature sensor, a blood pressure sensor, an EEG monitor, an ECGmonitor, an blood oxygen saturation monitor, perfusion index sensor, andeye sclera color sensor, an airflow sensor, sweat-based biometricsensor, or a magnetic field monitor. In one specific aspect, the sensordevice or system can include a sensor system to monitor or detectmicro-visible physiological conditions and variations of an individualor subject, such as described in U.S. Pat. Nos. 9,913,583 and No.10,470,670, which are incorporated by reference in their entirety.Essentially, the sensor system can comprise a camera in communicationwith a processor. The camera is configured to capture at least a firstand second image of the subject. The processor comprises executable codeconfigured to amplify microscopic temporal variations between the firstand second image of the subject. The physiological variations caninclude, but are not limited to, changes in pulse, breathing rate, skincoloration, volume of sweat, body motions associated with a physiologicvariation, and others. The processor and executable code can further beconfigured to generate a profile of at least one microscopic temporallydetected physiological variation of the subject, and to compare theprofile of the subject to a pre-existing first aggregate profile of aplurality of third-party subjects, said aggregate profile correspondingto the at least one microscopic temporally detected physiologicalvariation of the third-party subjects, said aggregate third-partyprofile corresponding to a known state of the third-party subjects. Theprocessor is further configured to detect differences between theprofile of the subject and the aggregate profile of the plurality ofthird-party subjects and determine a probability that a state of thesubject corresponds to the known state of the third-party subjects. Inan alternative, the processor and executable code can be configured tocompare the profile of the subject to a pre-existing baseline aggregateprofile of the subject, said baseline aggregate profile corresponding tothe at least one microscopic temporally detected physiological variationof the portion of the subject. In this example, the processor andexecutable code can be further configured to detect differences betweenthe profile of the subject and the pre-existing baseline aggregateprofile of the subject.

A sensor device can include a wearable sensor device 108 (e.g., heartrate monitor, blood pressure monitor, pulse oximeter, microphone,camera, thermometer, etc.) that connects to the mobile computing device102 using a wired or wireless connection.

Health metrics can be generated from the sensor data received from thesensor devices. The health metrics can be securely captured and storedon the mobile computing device 102 in an encrypted form. For example,sensor data generated by a sensor device can be encrypted using anappropriate encryption technique and health metrics generated from thesensor data can be encrypted and stored on the mobile computing device102 (or another data repository as described later). The health metricscan be collected on the computing device 102 for a baseline time period.The length of the baseline time period may be anywhere from a few hoursto several days or weeks depending on the health metric. For example, abaseline time period for collecting body temperature data used tocalculate a baseline body temperature may be one (1) to two (2) days orless, including at the time of the third-party health status request,whereas a baseline time period for collecting blood pressure data usedto calculate a baseline blood pressure may be a week or more.

The health metrics collected by the mobile computing device 102 can beused to define baseline health metrics (e.g., health profiles) which canbe compared to current health metrics obtained from the sensor devicesto determine the health status of the person 104, as described in moredetail below. Baseline health metrics or health profiles can be definedfor individual physiological functions, such as baseline heart rate orprofile, baseline blood pressure or profile, baseline respiratory rateor profile, baseline blood oxygen saturation or profile, baselineperfusion index, baseline eye sclera color, baseline microscopictemporally detected physiological variations, etc. In one example,baseline health metrics can be evaluated together to form an overallbaseline health for the person 104. For example, body temperature,respiratory rate, and dehydration rate can be evaluated together todetermine whether the person 104 may have symptoms associated with adefined strain of a virus. Also, the baseline health metrics can beevaluated together to determine whether a deviation in one of thebaseline health metrics is normal or abnormal. For example, a rise inbody temperature can be evaluated against other baseline metrics (e.g.,blood pressure, oxygen saturation, etc.) to determine whether the risein body temperature indicates a health issue or is merely an anomaly,such as increased anxiety.

In one example, in the case that baseline health metrics are notavailable (e.g., during a baseline time period used to collect heathmetrics), public baseline health metrics can be used in place of theperson's baseline health metrics. The public baseline health metrics canbe an average of health metrics obtained from anonymous persons who havepersonal characteristics that are similar to the person 104.Illustratively, during a time that body temperature metrics are beingcollected to define a baseline body temperature for the person 104,physical characteristics of the person 104 (e.g., age, gender, weight,etc.) can be used to obtain a public baseline body temperature. Thepublic baseline body temperature can be used to determine a currenthealth status of the person 104 until a baseline body temperature hasbeen defined for the person 104.

After one or more baseline health metrics or profiles have been definedfor the person 104, the mobile computing device 102 can use the baselinehealth metrics to define a current health status for the person 104. Inone example, the current health status can be defined by comparing oneor more current health metrics to one or more baseline health metrics.The mobile computing device 102 can generate one or more current healthmetrics for the person 104 from sensor data obtained from the sensordevices connected to the mobile computing device 102. The types ofcurrent health metrics generated by the mobile computing device 102 maycorrespond to the types of baseline health metrics used to define thecurrent health status for the person 104. For example, a current bodytemperature metric can be captured and compared to a baseline bodytemperature metric, a current heart rate metric can be obtained andcompared to a baseline heart rate metric, a current microscopictemporally detected physiological variation metric can be obtained andcompared to a baseline microscopic temporally detected physiologicalvariation metric, and other types of current health metrics may beobtained and compared to corresponding types of baseline health metrics,as can be appreciated. In the case that the current health metricscorrespond to the baseline health metrics, the current health status ofthe person can be defined as healthy. In the case that the currenthealth metrics do not correspond to the baseline health metrics, thecurrent health of the person 104 can be defined as not healthy. In oneexample, a defined threshold (e.g., within +/−3%, +/−5%, or +/−10% of abaseline health metric) can be used to determine whether the currenthealth metrics correspond to the baseline health metrics. If the currenthealth metrics are within the defined threshold(s), the person 104 maybe categorized as healthy, and if the current health metrics are outsideof the defined threshold(s), the person 104 may be categorized as nothealthy. When evaluated together, the defined thresholds for the currenthealth metrics can be adjusted based on the combination of currenthealth metrics being used. For example, a defined threshold for a singlecurrent health metric (e.g., body temperature) when used alone to definea current health status of a person 104 may be higher/lower than adefined threshold for the current health metric when the current healthmetric is considered in combination with other current health metrics(e.g., respiration rate). As an illustration, when considered alone, adefined threshold for body temperature may be >98.6 F., but whenevaluated in combination with a respiratory rate, the defined thresholdfor body temperature may be >100.4 F.

After a current health status has been defined for the person 104, acertification message 110 can be generated at the mobile computingdevice 102. In one aspect, the certification message 110 can bepresented to a third-party 106 (e.g., third-party overseeing point ofaccess admittance, such as transportation security or event/localehealth check) to, for example, certify that the current health status ofthe person 104 is acceptable in association with or as part of adetermination by the third-party as to whether or not to permit theperson 104 to access or be admitted to a restricted or protected area,activity, locale, object etc. overseen by the third-party. As anexample, prior to boarding public transportation or entering acontrolled venue, the person 104 may be requested to present acertification of health indicating that the person 104 is not in dangerof transmitting an infectious disease. In response, the person 104, viathe mobile computing device 102, may obtain a current health status forthe person 104 (i.e., themselves) and generate a certification message110 on the mobile computing device 102 that indicates a current statusof health of the person 104. The certification message 110 can be avisual indicator shown on a display screen of the mobile computingdevice 102. For example, the certification message 110 can be a visualicon, a visual code, a bar code, a two-dimensional (2D) bar code (e.g.,QR code), an alpha-numeric code, or a color code (e.g., green or redcode) shown on a display screen of the mobile computing device 102.

In one example configuration, the certification message 110 can be sentto a third-party device (not shown). The certification message 110 maybe sent using RF (radio frequency) communication (e.g., BLUETOOTH, WIFI,cellular network, near-field-communication (NFC), and the like). In oneexample, a photograph of the person can be provided with thecertification message 110 to enable the third-party 106 to verify theidentity of the person 104.

In another example, a current health status for the person 104 can bepresented as a defined probability of the person's health. In oneexample configuration, a defined probability (e.g., 82% chance of goodhealth) can be an overall probability that the person 104 is healthy ornot healthy. The defined probability can be calculated using a pluralitycurrent health metrics for the person 104 and a probability thresholdthat represents a baseline health for the person 104. The probabilitythreshold may be based in part on baseline health metrics for the person104 and a deviation from the baseline health metrics, which if exceeded,indicates an unhealthy state of the person 104. As will be appreciated,a healthy state and an unhealthy state may be defined for individualpersons, where baseline health metrics or profiles for an individualperson may define a healthy state, and a deviation from the baselinehealth metrics or profiles may be defined as an unhealthy state for theindividual person. The defined probability of health can be displayed atthe mobile computing device 102, which can be presented to a third-party106, or the defined probability of health can be sent to the third-party106 using RF communication.

In another example configuration, a defined probability can be aprobability that the person 104 has a particular health condition (e.g.,influenza, common cold, pneumonia, coronavirus, adenovirus, mono virus,etc.). The defined probability can be calculated using current healthmetrics associated with symptoms of the health condition and aprobability threshold, which if not exceeded, indicates a likelihoodthat the person 104 has the health condition. For example, a healthcondition profile can be created for a particular health condition(e.g., influenza, common cold, pneumonia, coronavirus, etc.), andcurrent health metrics for the person 104 can be compared to the healthcondition profile to determine a defined probability that the person 104has the health condition. The health condition profile may specifyhealth metrics associated with symptoms of the health condition andprovide the probability threshold(s) for the health condition. Thehealth condition profile can be provided to the mobile computing device102 and in response to a request, the mobile computing device 102 mayobtain current health metrics specified by the health condition profileand calculate a defined probability whether the person has the healthcondition. For example, if a defined number of the current healthmetrics (e.g., a majority) are below the probability threshold, thedefined probability may indicate that the person 104 likely has theparticular condition (e.g., influenza, common cold, pneumonia,coronavirus, etc.). The defined probability can be displayed at themobile computing device 102 to indicate whether the person 104 likelyhas the particular condition, and/or the defined probability can be sentto a third-party 106 to provide an indication whether the person 104likely has the particular condition.

FIG. 2 is a block diagram illustrating an example system environment 200in which the present technology may be executed. The system environment200 may include a mobile computing device 202 that is in communicationwith one or more sensor devices 228. The mobile computing device 202 mayinclude any mobile device capable of obtaining sensor data from sensordevices 228 and calculating health metrics using the sensor data. Themobile computing device 202 may be a smart phone, a smart watch, adigital assistant, a mobile internet device, a tablet computer, a laptopcomputer, or other mobile devices with like capability. In one exampleconfiguration, the mobile computing device 202 may be a wearable device,such as a smartwatch, medical device, smart eyewear, smart clothing, andthe like containing sensor devices 228 configured to generate sensordata used to generate health metrics.

Sensor devices 228 may be contained in the mobile computing device 202and/or may be in wired or wireless communication with the mobilecomputing device 202. The sensor devices 228 can include, but are notlimited to: a camera sensor, a heart rate sensor, a respiration ratesensor, an acoustic emission sensor, a temperature sensor, a bloodpressure sensor, an EEG sensor, an ECG sensor, an blood oxygensaturation sensor, a perfusion index sensor, an eye sclera color sensor,an airflow sensor, a sweat-based biometric sensor, a magnetic fieldsensor, a microscopic temporal physiological variation sensing system,and other sensor devices/systems. The sensor devices 228 can beconfigured to capture sensor data, from which health metrics can becalculated. For example, image data from a earners sensor can be used togenerate skin pigmentation metrics, eye sclera color metrics, ormicroscopic temporal physiological variation-derived metrics, ECG datacan be used to generate electrical heart activity metrics, EEG data canbe used to generate electrical brain activity metrics, acousticsemission data can be used to generate respiratory sound metrics, pulseoximeter data can be used to generate blood oxygen saturation metrics,respiration rate metrics, and perfusion index metrics, temperature datacan be used to generate body temperature metrics, and sweat data can beused to generate sweat loss metrics. As will be appreciated, the presenttechnology is not limited to the types of health metrics describedabove. Any type of health metric that may be useful in defining acurrent health status of a person is within the scope of the disclosure.

The mobile computing device 202 can include one or more memory modules204 configured to store processing modules, which may include a healthmetrics collection module 206, a baseline metrics module 208, a healthcertification module 210, and other modules. Also, the memory modules204 may be used to store health metrics 212 in a health metrics datastore 230, and store baseline health profiles 214 in a health profilesdata store 232.

The health metrics collection module 206 can be configured to collecthealth metrics 212 used to define baseline health metrics and createbaseline health profiles 214. The health metrics collection module 206may be configured to periodically obtain sensor data from a sensordevice 228 and generate a health metric from the sensor data. As anexample, the health metrics collection module 206 may obtain sensor datafrom a heart rate sensor and generate a heart rate metric using thesensor data. The health metrics collection module 206 may encrypt thehealth metrics using an encryption technique and store the encryptedhealth metrics 212 to a metrics data store 230 located in the memorymodules 204 of the mobile computing device 202. The health metrics 212may include metadata describing a type of health metric and a date thatthe health metric 212 was created. The stored health metrics 212 may beused by the baseline metrics module 208 to calculate baseline healthmetrics for a person, as described below. In one example, the healthmetrics collection module 206 may be configured to manage health metrics212 stored on the mobile computing device 202 by purging older healthmetrics 212 from the health metrics data store 230 (e.g., health metricsolder than one, three, six months, etc.).

In one example, the mobile computing device 202 may be in networkcommunication with a data repository 234 and the health metricscollection module 206 may send the health metrics 212 to the datarepository 216 to allow the health metrics 212 to be stored at the datarepository 234. A data repository 234 may be a cloud repository, ahealth care provider repository, a service provider environment, a datawarehouse, an at-home computing device, or another type of datarepository.

The baseline metrics module 208 can be configured to define baselinehealth metrics using health metrics 212 stored in the health metricsdata store 230. The baseline metrics module 208 may define baselinehealth metrics for physiological states, such as: body temperature,heart rate, blood pressure, respiratory rate, blood oxygen saturation,eye sclera color, perfusion index, microscopic temporal physiologicalvariation detected conditions that correlate with states, such as aphysical condition (e.g., heart attack, infectious disease, etc.), amental condition (e.g., aggravated psychosis), or an emotional condition(e.g., severe depression), and other physiological states. In oneexample, the baseline metrics module 208 may obtain a set of healthmetrics 212 from the health metrics data store 230 and calculate abaseline health metric using the set of health metrics 212. The baselinehealth metric may be an average of health metric values included in theset of health metrics. For example, the baseline metrics module 208 maycalculate a baseline average by totaling the values of the health metricentries in the set of health metrics and dividing the sum by the numberof entries in the set of health metrics.

In one aspect, weights can be assigned to deviations from baselinehealth metrics, where an assigned weight can reflect a dependability ofhaving a deviation in a particular current health metric, and theweights can be summed to define a current health status for a person.For example, when used together to define a current health status, adeviation from a body temperature baseline may be weighted more or lessthan a deviation from a respiration baseline. In one configuration, theweighting can be dynamic. As an example, deviations in current healthmetrics which are indicatively linked to a health condition may beevaluated together to dynamically increase or decrease a weighting basedon the relationship of the current health metrics to the healthcondition. For example, when both body temperature and respiration ratedeviate a certain amount from baseline health metrics, the deviationwhen considered together may be more indicative of a health condition ascompared to the individual deviations of the heath metrics, andtherefore, the weighting(s) assigned to the health metrics may beincreased or decreased accordingly.

In another example, the baseline metrics module 208 can be configured tocreate health profiles 214 for a person. A health profile 214 may bebased on a plot of health metrics spaced over a time period depicting aphysiological state of a person during the time period. As anillustration, a pulmonary profile for a person may be based onrespiration metrics and acoustic emission metrics collected over a timeperiod. The pulmonary profile may provide a higher-level overview of apulmonary state for a person based on combined respiration rate metricsand respiratory sound metrics. The health profiles 214 can be stored ina health profile data store 232. In one example, the healthcertification module 210 can be configured to define a current healthstatus for a person and generate a certification message that certifiesthe current health of the person to a third-party. The healthcertification module 210 may receive requests for a current healthstatus for a person. The person may be a user or owner of the mobilecomputing device 202 and the person may request the current healthstatus via a user interface for the mobile computing device 202. Forexample, the mobile computing device 202 may include a touchscreen and agraphical user interface displayed on the touchscreen may allow theperson to select a graphical control provided to request the currenthealth status.

In response to a request for a current health status of the person, thehealth certification module 210 may obtain current health metrics forthe person from one or more of the sensor devices 228 contained in,and/or connected to, the mobile computing device 202. The healthcertification module 210 may use the current health metrics to define acurrent health status for the person. For example, the healthcertification module 210 can compare the current health metrics to abaseline health state for the person and determine whether the currenthealth metrics correspond to the baseline health state. The baselinehealth state of a person may be based on one or more baseline healthmetrics 212, health profiles 214, and/or patient health records 218associated with the person. Illustratively, the health certificationmodule 210 may define a current health status of a person as healthywhen one or more of the current health metrics correspond to a baselinehealth state of the person, and define the current health status of theperson as unhealthy when one or more of the current health metricsdeviate from the baseline health state of the person. For example, acurrent health status of a person may be defined as healthy when currenthealth metrics for the person are substantially the same ascorresponding baseline health metrics for the person (e.g., the currenthealth metrics are within a defined threshold or range e.g., within+/−2%, +/−5%, or +/−7% of the baseline health metrics). The currenthealth status of the person may be defined as unhealthy when the currenthealth metrics for the person are not substantially the same as thebaseline health metrics for the person (e.g., outside of the definedthreshold or range of the baseline health metrics). As describedearlier, when evaluated together, defined thresholds for current healthmetrics can be adjusted based on the combination of health metrics beingused to define the current health of the person, and deviations ofcurrent health metrics front baseline health metrics can be weighted.

The health certification module 210 can be configured to generate acertification message indicating the defined current health status of aperson. In one example, the health certification module 210 can outputthe certification message as a visual indicator and an operating systemexecuted on the mobile computing device 202 may render the certificationmessage on a display screen of the mobile computing device 202 which canbe shown to a third-party. Illustratively, the certification message canbe presented as a visual code, a bar code, a 2D bar code, analpha-numeric code, or a color code on the display screen of the mobilecomputing device 202. In another example, the health certificationmodule 210 can be configured to send the certification message (e.g.,wired or wirelessly) to another device to allow a third-party to viewthe certification message.

In another example, the health certification module 210 can beconfigured to define a probability of health of a person and generate amessage indicating the probability of health, which can be provided to athird-party. The defined probability can be an overall probability thatthe person is healthy or not healthy. The health certification module210 may receive requests for a defined probability of health for aperson, who may be a user or owner of the mobile computing device 202.In response to a request for a defined probability of health for aperson, the health certification module 210 may obtain current healthmetrics from one or more of the sensor devices 228 contained in, and/orconnected to, the mobile computing device 202. The health certificationmodule 210 may use the current health metrics and a probabilitythreshold or probability thresholds related to a baseline health of theperson to calculate the defined probability of health of the person. Theprobability threshold used to calculate the defined probability ofhealth can be based in part on baseline health metrics for the personand a deviation from the baseline health metrics (e.g., 90^(th),80^(th), 70^(th), percentile deviation), which if exceeded, indicates anunhealthy state of the person. In one example, the probabilitythresholds can be adjusted based on a combination of current healthmetrics being used to define a current health of the person, anddeviations of the current health metrics from the baseline healthmetrics can be weighted as described earlier. As described earlier, adefined probability in one example can be a probability that a personhas a particular health condition (e.g., influenza, common cold,pneumonia, coronavirus, etc.). The health certification module 210 canbe configured to calculate a defined probability for a health conditionusing current health metrics associated with symptoms of the healthcondition and a probability threshold for the condition, which ifexceeded, indicates a likelihood that the person has the healthcondition. For example, a health condition profile 216 (e.g., influenzaprofile, pneumonia profile, coronavirus profile, etc.) can be createdfor a particular health condition, and the health condition profile 216can be used to determine a defined probability of the health condition.Health condition profiles 216 can be stored in a health profile datastore 236 located on the mobile computing device 202 or in anotherlocation (e.g., data repository 234). A health condition profile 216 mayspecify health metrics 212 associated with symptoms of a particularhealth condition and specify a probability threshold for the healthcondition (e.g., one or more health metric thresholds or rangesassociated with health condition symptoms) that, if exceeded, indicatesa likelihood that a person has the health condition. For example, ahealth condition profile 216 may define influenza symptoms (e.g., bodytemperature and cough) and probability thresholds for the flu symptoms(body temperature >100° and detected cough >2 per hour). If currenthealth metrics for a person exceed the probability thresholds, adetermination can be made that the person has the influenza.

In response to a request for a defined probability of a health conditionfor a person, the health certification module 210 may obtain a healthcondition profile 216 associated with the health condition and obtaincurrent health metrics specified by the health condition profile 216.The health certification module 210 can then calculate a definedprobability whether the person has the health condition using thecurrent health metrics using a probability threshold for the healthcondition specified in the health condition profile 216. The healthcertification module 210 can be configured to output the definedprobability of the health condition to the mobile computing device 202(e.g., as a percentage, a visual code, a bar code, a 2D bar code, analpha-numeric code, a color code, etc.), such as for display to athird-party, or to send the defined probability of the health conditionto another device to allow a third-party to view the definedprobability. For example, the output may be that there is a 90% chancethe owner of the device has the health condition or there is a 10%chance the owner of the device has the health condition being targeted.

The mobile computing device 202 may include hardware processor devices222, Input/Output (I/O) communication devices 224 to enablecommunication between hardware devices and sensor devices 228.Networking devices 226 may be provided for communication across anetwork 220 with one or more remote computing devices, sensors 226,and/or data repositories 234. The networking devices 226 may providewired or wireless networking access. Examples of wireless network accessmay include cellular network access, WI-FI network access, BLUETOOTHnetwork access, or similar network access. In one example, the mobilecomputing device 202 can include a display, such as a touchscreen thatdisplays an interactive graphical user interface.

The network 220 may include any useful computing network, including anintranet, the Internet, a local area network, a wide area network, awireless data network, or any other such network or combination thereof.Components utilized for such a system may depend at least in part uponthe type of network and/or environment selected. Communication over thenetwork may be enabled by wired or wireless connections and combinationsthereof. While FIG. 2 illustrates an example of a system environmentused to implement the techniques above, many other similar or differentenvironments are possible. The example system environments discussed andillustrated above are merely representative and are not meant to belimiting.

FIG. 3 is a diagram that illustrates another example system environment300 in which the present technology may be executed. The systemenvironment 300 can include a mobile computing device 310 used by athird-party 312 to obtain current health metrics for a person 314 and tosend the current health metrics to a data center 302 where the currenthealth metrics can be used to define a current health status for theperson 314. The mobile computing device 310 can be a smart phone, adigital assistant, a smart watch, a mobile internet device, a tabletcomputer, a laptop computer, or other mobile devices capable of beingused by a third-party to obtain current health metrics for a person 314.

In one example, the mobile computing device 310 can include one or moresensor devices and/or can be connected to one or more sensor devices viaa wired or wireless connection. Sensor data received from the sensordevices can be used by the mobile computing device 310 to generatecurrent health metrics for the person 314. The mobile computing device310 can send the current health metrics and a personal identifier forthe person 314 (e.g., personally identifiable information,bio-identifier, photograph, etc.) over a network 308 to the data center302. The current health metrics sent to the data center 302 may beencrypted using a data encryption technique, such as asymmetricencryption. The data center 302 can be: a health care data center, clouddata center, colocation data center, managed services data center, oranother type of data center. The data center 302 may host a healthcertification service 320 along with historical health metrics 306and/or patient health records 304 for the person 314.

The current health metrics received at the data center 302 can beprovided to the health certification service 320 hosted in the datacenter 302. The health certification service 320 can be configured todetermine a current health status for a person 314 and generate acertification message that certifies the current health status for theperson 314. In one example, the health certification service 320identifies historical health metrics 306 and/or patient health records304 associated with the person 314 using the personal identifierincluded with the current health metrics, and the health certificationservice 320 decrypts the current health metrics received from the mobilecomputing device 310 and compares the current health metrics to thehistorical health metrics 306 and/or patient health records associatedwith the person 314. As described earlier, current health metrics for aperson 314 can be compared to baseline health metrics for the person 314to define a current health status for the person 314. If the currenthealth metrics correspond to the baseline health metrics (e.g., within athreshold), then the current health status of the person 314 can bedefined as healthy. In the case that the current health metrics do notcorrespond to the baseline health metrics, the current health status ofthe person 314 can be defined as unhealthy.

After defining a current health status of the person 314, the healthcertification service 320 generates a certification message 316 andsends the certification message 316 to the mobile computing device 310.In response to receiving the certification message 316, the mobilecomputing device 310 displays the certification message 316 on a displayscreen to allow the third-party 312 to view the certification message316. Accordingly, the certification message 316 can certify to thethird-party 312 the current health status of the person 314. In oneexample, the health certification service 320 can obtain a photograph ofthe person 314 (e.g., from a patient health record 304) and send thephotograph with the certification message 316 to the mobile computingdevice 310. The third-party 312 can use the photograph to verify theidentity of the person 314. Also, in one example, biometrics (e.g.,facial recognition, fingerprint recognition, and the like) can be usedto verify the identity of the person 314. The health certificationservice 320 can obtain biometrics from a sensor (e.g., camera,fingerprint reader, etc.) and compare the biometrics with biometric datafor the person 314 obtained from a certified file and/or accessremotely-held identification data to create a form of two-factor IDcertification. In one example, a blockchain technique can be used tostore and obtain personally identifying information for the person 314which can be used to verify the identity of the person 314.

FIG. 4 is a diagram that illustrates yet another example systemenvironment 400 in which the present technology may be executed. Thesystem environment 400 can include a health check station 412 or kioskcontaining sensor devices 414 and computing resources (e.g., aprocessor, computer memory, and network devices) which can be used toobtain current health metrics for a person 410 and send the currenthealth metrics to a data center 402. Sensor devices/systems 414 includedin the health check station 412 can include: a camera sensor, a heartrate sensor, a respiration rate sensor, an acoustic emission sensor, atemperature sensor, a blood pressure sensor, an EEG monitor, an ECGmonitor, a blood oxygen saturation monitor, a perfusion index sensor, anairflow sensor, sweat-based biometric sensor, a magnetic field monitor,a microscopic temporal physiological detection system and other types ofsensor devices. The computing resources included in the health checkstation 412 can be used to generate current health metrics from sensordata obtained from the sensor devices 414.

In one example, a person 410 can step up to, or into, the health checkstation 412 and one or more sensor devices 414 (e.g., an infraredthermometer, a pulse oximeter, a blood pressure monitor, and/or a cameradevice) can be used to obtain current health metrics for the person 410(e.g., body temperature, blood oxygen saturation, blood pressure, skinpigmentation). The health check station 412 can encrypt the currenthealth metrics and send the encrypted current health metrics to a datacenter 402 that hosts a health certification service 420. The healthcertification service 420, as described above in association with FIG.3, can be configured to define a current health status for a person 410by comparing the current health metrics (e.g., body temperature, bloodoxygen saturation, blood pressure, skin pigmentation) to historicalhealth metrics 406 and/or patient health records 404 (e.g., baselinebody temperature, baseline blood oxygen saturation, baseline bloodpressure, baseline skin pigmentation, diagnosed health condition (e.g.,high-blood pressure, diabetes, etc.)). If the current health metricscorrespond to baseline health metrics and/or health profiles for theperson 410, then the current health status of the person 410 can bedefined as healthy. In the case that the current health metrics do notcorrespond to the baseline health metrics and/or health profiles, thecurrent health status of the person 410 can be defined as unhealthy.

After defining the current health status for the person 410, the healthcertification service 420 can generate a certification message whichcertifies the current health status for the person 410. In one exampleconfiguration, the health certification service 420 can send thecertification message over the network 408 to the health check station412. The health check station 412 can include a display 416 (e.g., adisplay screen) on which the certification message can be displayed,allowing a third-party 418 to view the certification message. In anotherexample configuration, the health certification service 420 can send thecertification message over the network 408 to a third-party device(e.g., mobile computing device, server, workstation, etc.) located at aremote location to allow a third-party to remotely view thecertification message. In another example, the certification message canbe sent to the person's smart phone, smart watch, tablet, laptop,digital assistant, mobile internet device, or wearable device, whichcould then be presented to the third party 418. In yet another exampleconfiguration, the health check station 412 can act as a physicalgateway to a restricted area (e.g., an airport terminal), and the healthcheck station 412 may allow access to the restricted area when acertification message received from the health certification serviceindicates that a current health status for a person 410 is healthy.Also, the health certification service 420 can be configured to verify aperson's identity using any of the identification techniques describedearlier.

The various processes and/or other functionality described inassociation with FIGS. 3-4 may be executed on one or more processorsthat are in communication with one or more memory modules. The datacenter depicted in FIGS. 3-4 may include a number of computing devicesthat are arranged, for example, in one or more server banks or computerbanks or other arrangements. The computing devices may support acomputing environment using hypervisors, virtual machine monitors (VMMs)and other virtualization software. The term “data store” may refer toany device or combination of devices capable of storing, accessing,organizing and/or retrieving data, which may include any combination andnumber of data servers, relational databases, object oriented databases,cluster storage systems, data storage devices, data warehouses, flatfiles and data storage configuration in any centralized, distributed, orclustered environment. The storage system components of a data store mayinclude storage systems such as a SAN (Storage Area Network), cloudstorage network, volatile or non-volatile RAM, optical media, orhard-drive type media. The data store may be representative of aplurality of data stores as can be appreciated.

API calls, procedure calls or other network commands that may be made inrelation to the health certification service included in the data centerdepicted in FIGS. 3-4 may be implemented according to differenttechnologies, including, but not limited to, Representational statetransfer (REST) technology or Simple Object Access Protocol (SOAP)technology. REST is an architectural style for distributed hypermediasystems. A RESTful API (which may also be referred to as a RESTful webservice) is a web service API implemented using HTTP and RESTtechnology. SOAP is a protocol for exchanging information in the contextof Web-based services.

FIGS. 3-4 illustrate that certain processing services may be discussedin connection with this technology and these services may be implementedas processing modules. In one example configuration, a module may beconsidered a service with one or more processes executing on a server orother computer hardware. Such services may be centrally hostedfunctionality or a service application that may receive requests andprovide output to other services or consumer devices. For example,modules providing services may be considered on-demand computing thatare hosted in a server, virtualized service environment, grid or clustercomputing system. An API may be provided for each module to enable asecond module to send requests to and receive output from the firstmodule. Such APIs may also allow third parties to interface with themodule and make requests and receive output from the modules.

FIG. 5 is a flow diagram illustrating an example method 500 forproviding a determination regarding a person's health while maintainingprivacy. As in block 502, health metrics can be collected for a person.In one example configuration, a person's mobile computing device can beused to collect health metrics for the person from sensor devicescontained in, and/or connected to, the mobile computing device. Thehealth metrics can be encrypted and stored on the mobile computingdevice. Alternatively, the mobile computing device may encrypt thehealth metrics and send the encrypted health metrics to a datarepository (e.g., a health care data repository, a cloud datarepository, an at-home computer, etc.) where the encrypted healthmetrics may be stored. In another example, one or more wearable sensordevices (e.g., fitness tracker, wearable heart rate sensor, wearablethermometer, wearable blood pressure monitor, etc.) can send sensor datato a computing device (e.g., a health care server, an at-home computer,a cloud service, etc.) used to collect and store health metrics for theperson. The health metrics for the person can be collected during abaseline time period (e.g., 1, 3, 10 weeks, etc.) to allow a sufficientamount of information to be gathered to calculate baseline healthmetrics for the person.

As in block 504, the health metrics collected by the mobile computingdevice can be used to define baseline health metrics for the person. Thebaseline health metrics can be defined for individual physiologicalfunctions, such as a baseline body temperature, a baseline heart rate, abaseline blood pressure, a baseline respiratory rate, a baseline bloodoxygen saturation, a baseline perfusion index, a baseline eye scleracolor, a baseline skin pigmentation, etc. In one example, baselinehealth metrics can be evaluated together to form an overall baselinehealth profile for the person. In one example, one or more baselinehealth profiles can be created for a person. A baseline health profilecan be based on a plot of health metrics spaced over a time period. Thebaseline health profile can provide a physiological state of the personduring the time period. The baseline health profile can be encrypted andstored on the mobile computing device or in a health profile data storelocated in a data repository.

As in block 506, a request for a current health status can be receivedat a mobile computing device via a user interface of the mobilecomputing device (or alternatively at a health check station as shown inFIG. 4). In response to the request, the mobile computing device canobtain one or more current health metrics that correspond to thebaseline health metrics defined for the person, as in block 508, Forexample, the mobile computing device (or health check station) cangenerate current health metrics using sensor data obtained from thesensor devices contained in, and/or connected to, the mobile computingdevice. As in block 510, a current health status for the person can bedetermined using the current health metrics and baseline health metricsassociated with the person. In one example configuration, one or morehealth profiles associated with the person can also be used to definethe current health status for the person. The current health status forthe person can be determined at the mobile computing device (or healthcheck station), or the current health metrics can be sent to a healthcertification service via a computer network and the healthcertification service can determine the current health status for theperson using the current health metrics.

The current health status for the person can be defined by comparing thecurrent health metrics to the baseline health metrics (and/or the healthprofiles associated with the person). In one example, the current healthstatus may be defined or determined using a binary value indicating thatthe person is either healthy or unhealthy. The current health status ofthe person may be set to a value indicating “healthy” when the currenthealth metrics correspond to the baseline health metrics, and thecurrent health status may be set to a value indicating “unhealthy” whenone or more of the current health metrics deviate from the baselinehealth metrics. In one example, a defined threshold can be used todetermine the current health status. As described earlier, whenevaluated together, defined thresholds for current health metrics can beadjusted based on the combination of health metrics being used to definethe current health of the person, and deviations of current healthmetrics from baseline health metrics can be weighted. If the currenthealth metrics are within the defined threshold, the current healthstatus may be set to “healthy”, and if the current health metricsdeviate from the baseline health metrics, the current health status maybe set to “unhealthy”.

After the current health status has been defined for the person, acertification message can be generated to certify the current healthstatus for the person. As in block 512, in the case that the currenthealth status of the person leads to a determination that the person ishealthy, then as in block 514, a certification message can be generatedto indicate that the person is healthy. In the case that the currenthealth status of the person leads to a determination that the person isunhealthy, then as in block 516, a certification message can begenerated to indicate that the person is unhealthy. In one exampleconfiguration, the certification message can be generated at the mobilecomputing device (or at a health check station) and the certificationmessage can be displayed on the mobile computing device (or health checkstation), as in block 518. In another example configuration, thecertification message can be generated by a health certification servicewhich sends the certification message to the mobile computing device (orhealth check station) over a computer network, and the certificationmessage can be displayed on the mobile computing device (or health checkstation), as in block 518.

The certification message can be visual indicator such as a visual icon,a visual code, a bar code, a 2D bar code, an alpha-numeric code, or acolor code. The certification message can be viewed by the person, suchthat the person can be aware of the person's current health status andwhether it is advisable for the person to enter a public space. Also,the certification message can be provided to a third-person (e.g., via adisplay screen of the mobile computing device or health check station orvia sending the certification message electronically to a third-personcomputing device) to allow the third-person to view the certificationmessage certifying the current health status for the person.

FIG. 6 illustrates a computing device 610 on which modules of thistechnology may execute. A computing device 610 is illustrated on which ahigh-level example of the technology may be executed. The computingdevice 610 may include one or more processors 612 that are incommunication with memory devices 620. The computing device 610 mayinclude a local communication interface 618 for the components in thecomputing device 610. For example, the local communication interface 618may be a local data bus and/or any related address or control busses asmay be desired.

The memory device 620 may contain modules 624 that are executable by theprocessor(s) 612 and data for the modules 624. In one example, thememory device 620 may include a health metrics collection module, abaseline metrics module, a health certification module, and othermodules. The modules 624 may execute the functions described earlier. Adata store 622 may also be located in the memory device 620 for storingdata related to the modules 624 and other applications along with anoperating system that is executable by the processor(s) 612.

Other applications may also be stored in the memory device 620 and maybe executable by the processor(s) 612. Components or modules discussedin this description may be implemented in the form of software usinghigh-level programming languages that are compiled, interpreted orexecuted using a hybrid of the methods.

The computing device 610 may also have access to I/O (input/output)devices 614 that are usable by the computing device 610. Networkingdevices 616 and similar communication devices may be included in thecomputing device 610. The networking devices 616 may be wired orwireless networking devices that connect to the internet, a LAN, WAN, orother computing network.

The components or modules that are shown as being stored in the memorydevice 620 may be executed by the processor(s) 612. The term“executable” may mean a program file that is in a form that may beexecuted by a processor 612. For example, a program in a higher levellanguage may be compiled into machine code in a format that may beloaded into a random access portion of the memory device 620 andexecuted by the processor 612, or source code may be loaded by anotherexecutable program and interpreted to generate instructions in a randomaccess portion of the memory to be executed by a processor. Theexecutable program may be stored in any portion or component of thememory device 620. For example, the memory device 620 may be randomaccess memory (RAM), read only memory (ROM), flash memory, a solid statedrive, memory card, a hard drive, optical disk, floppy disk, magnetictape, or any other memory components.

The processor 612 may represent multiple processors and the memorydevice 620 may represent multiple memory units that operate in parallelto the processing circuits. This may provide parallel processingchannels for the processes and data in the system. The localcommunication interface 618 may be used as a network to facilitatecommunication between any of the multiple processors and multiplememories. The local communication interface 618 may use additionalsystems designed for coordinating communication such as load balancing,bulk data transfer and similar systems.

While the flowcharts presented for this technology may imply a. specificorder of execution, the order of execution may differ from what isillustrated. For example, the order of two more blocks may be rearrangedrelative to the order shown. Further, two or more blocks shown insuccession may be executed in parallel or with partial parallelization.In sonic configurations, one or more blocks shown in the flow chart maybe omitted or skipped. Any number of counters, state variables, warningsemaphores, or messages might be added to the logical flow for purposesof enhanced utility, accounting, performance, measurement,troubleshooting or for similar reasons.

Some of the functional units described in this specification have beenlabeled as modules, in order to more particularly emphasize theirimplementation independence. For example, a module may be implemented asa hardware circuit comprising custom VLSI circuits or gate arrays,off-the-shelf semiconductors such as logic chips, transistors, or otherdiscrete components. A module may also be implemented in programmablehardware devices such as field programmable gate arrays, programmablearray logic, programmable logic devices or the like.

Modules may also be implemented in software for execution by varioustypes of processors. An identified module of executable code may, forinstance, comprise one or more blocks of computer instructions, whichmay be organized as an object, procedure, or function. Nevertheless, theexecutables of an identified module need not be physically locatedtogether, but may comprise disparate instructions stored in differentlocations which comprise the module and achieve the stated purpose forthe module when joined logically together.

Indeed, a module of executable code may be a single instruction, or manyinstructions and may even be distributed over several different codesegments, among different programs and across several memory devices.Similarly, operational data may be identified and illustrated hereinwithin modules and may be embodied in any suitable form and organizedwithin any suitable type of data structure. The operational data may becollected as a single data set, or may be distributed over differentlocations including over different storage devices. The modules may bepassive or active, including agents operable to perform desiredfunctions.

The technology described here may also be stored on a computer readablestorage medium that includes volatile and non-volatile, removable andnon-removable media implemented with any technology for the storage ofinformation such as computer readable instructions, data structures,program modules, or other data. Computer readable storage media include,but is not limited to, a non-transitory machine readable storage medium,such as RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical storage, magneticcassettes, magnetic tapes, magnetic disk storage or other magneticstorage devices, or any other computer storage medium which may be usedto store the desired information and described technology.

The devices described herein may also contain communication connectionsor networking apparatus and networking connections that allow thedevices to communicate with other devices. Communication connections arean example of communication media. Communication media typicallyembodies computer readable instructions, data structures, programmodules and other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any information deliverymedia. A “modulated data signal” means a signal that has one or more ofits characteristics set or changed in such a manner as to encodeinformation in the signal. By way of example and not limitation,communication media includes wired media such as a wired network ordirect-wired connection and wireless media such as acoustic, radiofrequency, infrared and other wireless media. The term computer readablemedia as used herein includes communication media.

Reference was made to the examples illustrated in the drawings andspecific language was used herein to describe the same. It willnevertheless be understood that no limitation of the scope of thetechnology is thereby intended. Alterations and further modifications ofthe features illustrated herein and additional applications of theexamples as illustrated herein are to be considered within the scope ofthe description.

Furthermore, the described features, structures, or characteristics maybe combined in any suitable manner in one or more examples. In thepreceding description, numerous specific details were provided, such asexamples of various configurations to provide a thorough understandingof examples of the described technology. It will be recognized, however,that the technology may be practiced without one or more of the specificdetails, or with other methods, components, devices, etc. In otherinstances, well-known structures or operations are not shown ordescribed in detail to avoid obscuring aspects of the technology.

Although the subject matter has been described in language specific tostructural features and/or operations, it is to be understood that thesubject matter defined in the appended claims is not necessarily limitedto the specific features and operations described above. Rather, thespecific features and acts described above are disclosed as exampleforms of implementing the claims. Numerous modifications and alternativearrangements may be devised without departing from the spirit and scopeof the described technology.

What is claimed is:
 1. A method for providing a determination regardinga person's health while maintaining privacy, comprising: collecting, ata mobile computing device, one or more health metrics for a person fromsensor devices in communication with the mobile computing device duringa baseline time period; defining baseline health metrics and a baselinehealth status using the one or more health metrics; receiving a requestfor a current health status for the person; obtaining one or morecurrent health metrics for the person from one or more of the sensordevices in communication with the mobile computing device, wherein thecurrent health metrics are obtained during a current time period;comparing the current health metrics to the baseline health metrics todefine the current health status for the person; and generating acertification message at the mobile computing device to be provided incertifying the current health status for the person.
 2. The method as inclaim 1, further comprising determining a person is unhealthy when oneor more of the current health metrics deviate from the baseline healthmetrics by a defined threshold.
 3. The method as in claim 1, furthercomprising determining the current health status for the person when thecurrent health metrics as compared to the baseline health metrics resultin a defined probability for health.
 4. The method as in claim 3,further comprising determining that the person is healthy if the definedprobability exceeds a probability threshold or that the person is nothealthy if the defined probably is below a probability threshold.
 5. Themethod as in claim 1, further comprising adjusting a probabilitythreshold for a current health metric based on a combination of currenthealth metrics used to define the current health status for the person.6. The method as in claim 1, further comprising assigning a weight to adeviation of a current health metric from a baseline health metric basedon an expected deviation, wherein weights assigned to deviations of thecurrent health metrics are summed to define the current health statusfor the person.
 7. The method as in claim 1, further comprising:identifying current health metrics which are indicatively linked to ahealth condition; and dynamically assigning weights to deviations of thehealth metrics from the baseline health metrics based on a relationshipof the health metrics to the health condition.
 8. The method as in claim1, further comprising securely capturing the health metrics and storingthe health metrics in an encrypted form.
 9. The method as in claim 1,further comprising storing the baseline health metrics in a data storelocated on at least one of: the mobile computing device, an at-homecomputing device, a cloud repository, a health care provider repository,or a service provider environment.
 10. The method as in claim 1, furthercomprising presenting the certification message as a visual indicator onthe mobile computing device.
 11. The method as in claim 1, furthercomprising, verifying an identity of the person using biometricsobtained from a sensor device included in the mobile computing device.12. The method as in claim 1, further comprising storing personallyidentifying information for the person in a blockchain; and retrievingthe personally identifying information from the blockchain to verify anidentity of the person.
 13. The method as in claim 7, further comprisingpresenting the certification message as at least one of: a visual code,a bar code, a 2D bar code, an alpha-numeric code, or a color code on adisplay screen of the mobile computing device.
 14. The method as inclaim 1, further comprising sending the certification message to athird-party device via an RF (radio frequency) communication.
 15. Themethod as in claim 1, wherein the sensor devices are in the mobilecomputing device or are electrically networked with the mobile computingdevice.
 16. The method as in claim 1, wherein the sensor devicescomprise at least one of: a heart rate sensor, a respiration ratesensor, a quality of respiration sensor, a respiration profile sensor,an acoustic emission sensor, a temperature monitor, a skin colormonitor, a skin color pattern monitor, blood pressure sensor, a bloodpressure profile sensor, an EEG monitor, an ECG monitor, an blood oxygensaturation monitor, a perfusion index sensor, an eye sclera colorsensor, an airflow sensor, a microscopic temporal physiologicalvariation sensing system, or a magnetic field monitor.
 17. The method asin claim 1, further comprising generating a health metric profile usingsensor data generated by a sensor device.
 18. The method as in claim 12.wherein the health metric profile includes at least one of a bloodpressure profile created using blood pressure metrics obtained from ablood pressure sensor, a pulmonary profile created using pulmonarymetrics obtained from a pulmonary sensor, a heart rate profile createdusing heart rate metrics obtained from a heart rate sensor, or amicroscopic temporal physiological variation profile using microscopictemporal physiological variation metrics.
 19. The method as in claim 1,wherein the mobile computing device is a smart phone, smart watch,tablet, laptop, a digital assistant, a mobile internet device, or awearable device.
 20. A mobile computing device to provide adetermination regarding a person's health while maintaining privacy,comprising: at least one processor; a plurality of sensor devices tomonitor a person's medical metrics, wherein the plurality of sensordevices are in communication with the mobile computing device; at leastone memory device including a data store to store a plurality of dataand instructions that, when executed, cause the mobile computing deviceto: collect one or more health metrics for a person from the pluralityof sensor devices in communication with the mobile computing deviceduring a baseline time period; define baseline health metrics and abaseline health status using the one or more health metrics; receive arequest for a current health status for the person; receive currenthealth metrics for the person from the plurality of sensor devices incommunication with the mobile computing device, wherein the currenthealth metrics are obtained during a current time period; compare thecurrent health metrics to the baseline health metrics to define acurrent health status for the person; and display a certificationmessage certifying the person's current health status on a screen of themobile computing device to enable the certification message to beprovided to a third-party.
 21. The mobile computing device as in claim20, wherein the instructions of the at least one memory device furthercause the mobile computing device to securely capture the health metricsand store the health metrics in an encrypted form.
 22. The mobilecomputing device as in claim 20, wherein the instructions of the atleast one memory device further cause the mobile computing device topresent the certification message as a visual icon on the mobilecomputing device.
 23. The mobile computing device as in claim 20,wherein the instructions of the at least one memory device further causethe mobile computing device to present the certification message as atleast one of: a visual code, a bar code, a 2D bar code, an alpha-numericcode, or a color code on a display screen of the mobile computingdevice.
 24. The mobile computing device as in claim 20, wherein theinstruction of the at least one memory device further cause the mobilecomputing device to present a picture of the person with thecertification message.
 25. The mobile computing device as in claim 20,wherein the plurality of sensor devices comprise at least one of: aheart rate sensor, a quality of heart rate sensor, a respiration ratesensor, a quality of respiration sensor, a respiration profile sensor,an acoustic emission sensor, a temperature monitor, a skin colormonitor, a skin color pattern monitor, blood pressure sensor, a bloodpressure profile sensor, EEG monitor, ECG monitor, blood oxygensaturation monitor, a perfusion index sensor, an eye sclera colorsensor, an airflow sensor, a microscopic temporal physiologicalvariation sensing system, or a magnetic field monitor.
 26. Anon-transitory machine readable storage medium having instructionsembodied thereon, the instructions when executed by one or moreprocessors, cause the one or more processors to perform a process,comprising: receiving one or more health metrics for a person from aplurality of sensor devices in communication with a mobile computingdevice during a baseline time period; defining baseline health metricsand a baseline health status using the one or more health metrics;receiving a request for a current health status for the person;receiving current health metrics for the person from the plurality ofsensor devices in communication with the mobile computing device,wherein the current health metrics are obtained during a current timeperiod; comparing the current health metrics to the baseline healthmetrics to define a current health status for the person; and displayinga certification message certifying the current health status of theperson on a screen of the mobile computing device to enable thecertification message to be provided to a third-party.
 27. Thenon-transitory machine readable storage medium as in claim 26, theprocess further comprising displaying the certification message as atleast one of: a visual code, a bar code, a 2D bar code, an alpha-numericcode, or a color code on a display screen of a mobile computing device.28. The non-transitory machine readable storage medium as in claim 26,wherein the plurality of sensor devices comprise at least one of: aheart rate sensor, a quality of heart rate sensor, a respiration ratesensor, a quality of respiration sensor, a respiration profile sensor,an acoustic emission sensor, a temperature monitor, a skin colormonitor, a skin color pattern monitor, blood pressure sensor, a bloodpressure profile sensor, EEG monitor, ECG monitor, blood oxygensaturation monitor, a perfusion index sensor, an eye sclera colorsensor, an airflow sensor, a microscopic temporal physiologicalvariation sensing system, or a magnetic field monitor.